SynapCores — Graph + Vector + LLM in one database (free Community Edition)
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New — Native MCP + OpenClaw long-term memory<br>Graph + Vector + LLM + MCP.<br>One database. One query.<br>Free, single-binary install. Production-ready Community Edition. ~30 seconds to your first AI-augmented query.<br>$curl -fsSL https://get.synapcores.com | sh
Want to see it run first?Watch the 5 live demos<br>Prefer a packaged installer?All download options<br>★ 5 LIVE DEMOS★ 161 READY-TO-RUN RECIPES★ NATIVE MCP★ OPENCLAW MEMORY★ MACOS + LINUX + DOCKER★ OPEN COMMUNITY EDITION
One query. Three systems other databases need.<br>SynapCores unifies graph traversal, vector similarity, and LLM inference into a single execution engine.
GraphVectorIn-DB ML<br>synapcores · cypherone engine<br>> ▋
Same engine, three workloads — graph, vectors, and ML — each in one statement. Compose all three in a single query, too.
Graph traversal, HNSW vector similarity , and in-database ML aren't three services here — they're one execution engine. Each answers in a single statement, from microseconds for graph to a couple of milliseconds with embedding or model inference in the loop.<br>On Postgres that's pgvector + Apache AGE + a model server + your application code stitching them together. On SynapCores it's one query — and you can compose all three in a single MATCH.
Stack Comparison
StackSystemsRound-tripsPinecone + Postgres + OpenAI rerank3 + your service4–5Neo4j + external embedding + LLM3 + your service3–4SynapCores11
148 ready-to-run recipes. Pick one to try.<br>Each recipe is a self-contained markdown file with embedded SQL or Cypher. Run them locally, modify them, ship them.
graph<br>5 min
Hello GraphRAG<br>advanced
Combine vector similarity, graph traversal, and LLM scoring in one query.<br>docs/bulkRecipes/recipes/graph/016_graphrag_qna.md
graph<br>7 min
Fraud Ring Detection<br>intermediate
Detect circular money laundering patterns up to 4 hops in a transaction graph.<br>docs/bulkRecipes/recipes/graph/006_fraud_ring_detection.md
ml<br>5 min
Customer Churn ML<br>beginner
AutoML training and inference in one SQL statement.<br>docs/bulkRecipes/recipes/ml/002_customer_churn_prediction.md
graph<br>6 min
Knowledge Graph from Earnings Call<br>beginner
Send a CFO call transcript to /v2/graph/extract. Query entities seconds later.<br>docs/bulkRecipes/recipes/graph/017_extract_earnings_call.md
graph<br>10 min
Drug Repurposing<br>advanced
Walk drug-target-disease chains. Use SIMILAR_TO on mechanism embeddings.<br>docs/bulkRecipes/recipes/graph/025_drug_repurposing.md
graph<br>6 min
Semantic Patient Cohorts<br>beginner
Find clinical lookalikes by symptom embedding in real-time.<br>docs/bulkRecipes/recipes/graph/029_clinical_patient_similarity.md
See all 148 recipes
What's in Community Edition<br>Community Edition is a complete AI-native engine. Sales is an upgrade path, not a front door.
FeatureCommunityEnterpriseCore SQL EngineVector Search (HNSW)Graph Database (Cypher)AI / LLM IntegrationMCP Server (Model Context Protocol)Multimedia (PDF/AV)AutoMLMulti-node ClusteringRaft ReplicationFine-grained RBACAudit Logging (Scale)SSO / SAML / LDAPImmutable Tables
Where we're going: v1.6 (Q3 2026) targets binary wire protocol, shared buffer pool, and B-tree indexes for OLTP at PG scale.
Need clustering, RBAC, or production support?<br>The Enterprise Edition (EE) ships everything in CE plus mission-critical scale and security. Paid Enterprise Support is also available for CE deployments.
Scale<br>Multi-node clustering + Raft replication + CDC inbound from MySQL/Postgres binlog.
Security & Compliance<br>Fine-grained RBAC, SSO/SAML, LDAP, encryption-at-rest, audit logging, and immutable tables.
Performance<br>Binary wire protocol, shared buffer pool, row-store fast path (v1.6+).
Enterprise Support (also available for CE)<br>SLA-backed support for production CE deployments: prioritized bug fixes, custom feature work, roadmap input, and direct access to the engineering team. Buy support without buying EE.
Contact salesOr start free with Community Edition